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ABSTRACT<br />

Development of a multimodal probability <strong>de</strong>nsity function<br />

The trend of DBH distribution is an excellent referential to the forest study, native or<br />

manma<strong>de</strong> forests. Density Probability Functions can be satisfactorily used for that purpose.<br />

Therefore, the main objective of this research was to present a new math<strong>em</strong>atical mo<strong>de</strong>l,<br />

sufficiently flexible to represent two or more mo<strong>de</strong>s. As objective of evaluating the mo<strong>de</strong>l<br />

effectiveness, its adjustment was compared to the classic continuous probabilistic<br />

distributions (Gauss, Exponential, Gamma, Beta and Weibull), as well as Quadros and Spline<br />

Function. Three distinct diametric distributions were used: one for Brazilian Nut tree, with<br />

three mo<strong>de</strong>s and passing trough the origin, and two for Araucaria, with two mo<strong>de</strong>s, one<br />

passing trough the origin and the other no. The Exponential Distribution assumes just a<br />

<strong>de</strong>crescent form and is potentially viable when represent natural regeneration diametric data is<br />

<strong>de</strong>sirable; therefore it is not good to this research. The Gaussian Distribution, commonly used<br />

to represent diametric distributions, provi<strong>de</strong>d a non satisfactory result, because of its low<br />

flexibility, in which occur one mo<strong>de</strong>. The Weibull, Gamma and Beta Distributions were more<br />

flexible, but can not represent two or more mo<strong>de</strong>s. The mo<strong>de</strong>l <strong>de</strong>veloped by Quadros is more<br />

flexible, but it was not adherent to all data distributions observed in this work. The Spline<br />

Function presented a high flexibility, but the results were not satisfactory, as consi<strong>de</strong>ring the<br />

adjustment, as consi<strong>de</strong>ring the biological interpretation, since it generates negative<br />

probabilities and can not predict the occurrence of individuals in the higher diameter classes.<br />

The proposed mo<strong>de</strong>l was adherent to all diametric distributions, being capable to present two<br />

or more mo<strong>de</strong>s (easily impl<strong>em</strong>ented); it is flexible; it can or can not pass trough the origin; it<br />

has all characteristics of a <strong>de</strong>nsity probabilistic function (it is always positive, continuous and<br />

can be integrated in its domain), the average and variance can be obtained by means of<br />

calculus, according to the probabilistic distribution theory.<br />

Keywords: Probability distribution, Mo<strong>de</strong>, Forest, Araucaria angustifolia, Bertholletia<br />

excelsa.

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